Smelling Faults in Spreadsheets

Abreu, Rui; Cunha, Jácome; Fernandes, João Paulo; Martins, Pedro; Perez, Alexandre; Saraiva, João

doi:10.1109/icsme.2014.33

Cited by 32 publications

(37 citation statements)

References 29 publications

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“…By pin pointing the bad smells in a spreadsheet may help the user to find the errors contained in it [37], [38]. These smells can further be analyzed by a fault-localization algorithm which will point more precisely to the faults contained in a spreadsheet [39], [40]. All these potential solutions need, of course, to be empirically validated.…”

Section: Discussionmentioning

confidence: 99%

“…In fact, we have also proposed techniques [37] and tools [38] to find such spreadsheet problems. Moreover, we have devised a technique where the result of bad smell detection, that is, the set of cells identified as smelly, is used by a spectrum-based fault localization algorithm to better pinpoint the anomalous cells in a spreadsheet [39], [40].…”

Section: Related Workmentioning

confidence: 99%

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Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Cunha

Fernandes

Mendes

et al. 2015

IIEEE Trans. Software Eng.

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This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved. Finally, we have designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Cunha

Fernandes

Mendes

et al. 2015

IIEEE Trans. Software Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…$15.00 DOI: 10.1145/3183399.3183402 of fault prevention, e.g., in preventive maintenance or fault prediction. They transfer the idea of code smells [6] to the spreadsheet domain and represent heuristics that are designed to indicate potential problems in spreadsheets such as complex formulas, possibly missing inputs, and problematic dependencies [1,3,10,11].…”

Section: Introductionmentioning

confidence: 99%

Combining spreadsheet smells for improved fault prediction

Koch

Schekotihin

Jannach

et al. 2018

Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results

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Spreadsheets are commonly used in organizations as a programming tool for business-related calculations and decision making. Since faults in spreadsheets can have severe business impacts, a number of approaches from general software engineering have been applied to spreadsheets in recent years, among them the concept of code smells. Smells can in particular be used for the task of fault prediction. An analysis of existing spreadsheet smells, however, revealed that the predictive power of individual smells can be limited. In this work we therefore propose a machine learning based approach which combines the predictions of individual smells by using an AdaBoost ensemble classi er. Experiments on two public datasets containing real-world spreadsheet faults show signi cant improvements in terms of fault prediction accuracy.

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“…Nested-IF expressions happen when end users write an IF function inside another IF or nested-IF function. According to previous research [3][4][5][6][7], nested-IF formulae in speadsheets are complex, unreadable, errorprone, as well as hard to debug and maintain. ere are also a lot of online discussions about the harm of nested-IF formulae.…”

Section: Introductionmentioning

confidence: 99%

Automated refactoring of nested-IF formulae in spreadsheets

Zhang

Han

Hao

et al. 2018

Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

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Spreadsheets are the most popular end-user programming so ware, where formulae act like programs and also have smells. One well recognized common smell of spreadsheet formulae is nested-IF expressions, which have low readability and high cognitive cost for users, and are error-prone during reuse or maintenance. However, end users usually lack essential programming language knowledge and skills to tackle or even realize the problem. e previous research work has made very initial a empts in this aspect, while no e ective and automated approach is currently available.is paper rstly proposes an AST-based automated approach to systematically refactoring nested-IF formulae. e general idea is two-fold. First, we detect and remove logic redundancy on the AST. Second, we identify higher-level semantics that have been fragmented and sca ered, and reassemble the syntax using concise built-in functions. A comprehensive evaluation has been conducted against a real-world spreadsheet corpus, which is collected in a leading IT company for research purpose. e results with over 68,000 spreadsheets with 27 million nested-IF formulae reveal that our approach is able to relieve the smell of over 99% of nested-IF formulae. Over 50% of the refactorings have reduced nesting levels of the nested-IFs by more than a half. In addition, a survey involving 49 participants indicates that for most cases the participants prefer the refactored formulae, and agree on that such automated refactoring approach is necessary and helpful. 2

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Smelling Faults in Spreadsheets

Cited by 32 publications

References 29 publications

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Combining spreadsheet smells for improved fault prediction

Automated refactoring of nested-IF formulae in spreadsheets

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